Péter Reisinger

ACCase inhibitor herbicides – selectivity, weed resistance and fitness cost: a review

The worldwide application of the group of herbicides known as ACCase inhibitors is associated with the widespread appearance of resistant biotypes among weeds. Accordingly, ACCase inhibitor resistance has become the third most frequent type of weed resistance. ACCase (acetyl-coenzyme A carboxylase) inhibitors, which include aryloxyphenoxypropionate, cyclohexanedione and phenylpyrazolin herbicides, are applied postemergence to control weedy grasses. Their phytotoxicity is specifically attributed to the inhibition of lipid biosynthesis, while their selectivity is mainly due to the fact that they are able to block the eukaryote-type ACCase enzyme of Poaceae. Certain herbicides can be applied to cereals, because herbicide “safeners” allow the herbicides to be degraded metabolically. Resistance can evolve through both non-target and target-site processes, and many amino acid substitutions have been identified that result in resistance. Cross-resistance to different herbicides is also relatively common. Nevertheless, in many cases, it has been found that resistant biotypes show no reduction in fitness. Cycloxydim-tolerant maize, without genetic modification, is now used also in European farmland, and it can be a suitable alternative to transgenic herbicide tolerant crops when combined with herbicide rotation and monitoring for resistance.

Loss of Nutrients Caused by Excessive Weediness at the Early Stage of Maize Vegetation Period

Abstract The experiment was carried out in a field previously not exposed to herbicides, in which jimsonweed (Datura stramonium L.) and wild hemp (Cannabis sativa spp. spontanea) were the dominant weeds. Using sites identified with global positioning system (GPS) coordinates, changes in abundance of weeds in time were investigated. Before the trial in autumn, soil samples were taken for analysis. Nutrient uptake was determined and compared with the results of the spring plant examinations. One month after the sowing of maize (Zea mays L.), the total number of weeds and the number of weed species present at the sampling sites were determined, and aerial fresh and dry weights of the crop and weed plants were measured. Plant tissue samples were assayed for contents of nitrogen, phosphorus, potassium, and calcium, and data obtained from weedy and weed‐free control areas were compared. Similarly, maize yields were determined, and their dependence on plot weediness was evaluated. We found that uptake of large amounts of nutrients by jimsonweed and wild hemp at the early stage of the development of maize is an important factor in crop‐weed competition.

Effect of weediness on the water content of the soil: A field study

Abstract Maize is a vigorous and tall‐growing plant. Still, as a widely spaced crop, maize is highly susceptible to competition from weeds during its early growth period, with losses greater than 30% commonly reported. To characterize the nature of maize–weed competition, nutrient and water contents of maize and weed plants and the soil were determined in a field study. The experiment was carried out at Baracska, Hungary, in 2003, in a 9.2‐ha project area. Sampling areas (2×2 m in size, 21 altogether) were assigned, identified with global positioning system (GPS) coordinates, and left without weed control. After the emergence of maize, the frequency and density of weeds at the sampling sites were regularly determined, and samples of crop and weed plants and soil (from the depths of 0–20, 20–40, 40–60, 60–80, and 80–100 cm) were taken for analysis of water and nutrient contents. Three weed species were dominant: jimsonweed (Datura stramonium L.), broomcorn millet (Panicum miliaceum L.), and wild hemp (Cannabis sativa L.). A linear negative relationship was observed between the weediness and the water content in the top 20‐cm layer of the soil at the sampling areas.

Relationships Between Soil Characteristics and Weeds

Abstract Information technologies, such as the global positioning system and geographic information system, provide new opportunities for improving the efficiency of weed management, thereby resulting in a reduction in financial and environmental costs. Thus, an evaluation of data of systematic weed surveys carried out repeatedly at locations identified by geographical coordinates allows the establishment of relationships between weed associations and soil properties. Our quantitative survey targeted a 53‐ha agricultural field at Baracska, Hungary, with a total of 122 sampling sites. Soil properties (pH, texture, organic carbon, humus, and macro‐ and microelement contents [altogether 24 parameters]) were determined and weeds (frequency and density for 27 species) were recorded at the sampling sites. A distinct negative association between the crop yield (tightly linked to levels of nitrogen, phosphorus, and potassium fertilizers in the soil) and the total weed density at the sampling sites was demonstrated by principal component analysis of our data, indicating a good management of the project area that successfully increased the crop plants competitiveness with weeds.

Competitiveness and Precision Management of the Noxious Weed Cannabis sativa L. in Winter Wheat

Abstract Wild hemp (Cannabis sativa ssp. spontanea) is a rapidly spreading weed in Hungary that forms large and stable patches in most agricultural fields. To evaluate the dominance properties and the nutrient uptake of wild hemp, we carried out experiments in a 36‐ha agricultural field, using 80 evenly distributed sampling areas that were identified by GPS coordinates. Field maps of wild hemp infestations were formulated to determine the density and dominance of this weed, and plants were analyzed for macroelement (nitrogen, phosphorus, potassium, and calcium) contents. Wild hemp showed significant competitiveness against winter wheat, greatly reducing the availability of nutrients to the crop plant. After localizing patches of wild hemp and other weeds in the field by GPS coordinates, a weed contour map was created. These maps were divided into manageable blocks and a site‐specific weed control technology was designed to reduce herbicide use, thereby decreasing the costs and environmental impact of wild hemp control.

From traditional weed mapping to an autonomous robot: developments and results from Hungary

Seit dem Jahr 2000 entwickeln wir in Ungarn Techniken fur die teilflachenspezifische Unkrautbekampfung. Seit Beginn konzentrierten wir uns aus finanziellen Grunden auf die Erstellung von Unkrautverteilungskarten (Kartentechnik). Die Methode zur Nachauflauf-Unkrautbekampfung wurde fur Winterweizen entwickelt und beginnt mit der Unkrautkartierung und der Datennachbearbeitung von Informationen und endet mit der Erstellung von Applikationskarten mit GIS-Software. In den ersten funf Jahren haben wir die Methoden zur Unkrautkartierung entwickelt. Nach Experimenten und Berechnungen fanden wir die Losung in einer ungarischen Methode basierend auf dem Unkrautdeckungsgrad. Dabei wird das Feld in 0,5 Hektar grose Quadrate geteilt und der Unkrautdeckungsgrad wird fur jedes Quadrat erfasst. Die Informationen sind georeferenziert mit DGPSKoordinaten. Der Verarbeitungsalgorithmus berucksichtigt Deckungsgrade mit Fokussierung auf das Vorkommen von gefahrlichen Unkrautarten, wahlt die Zellen, in denen eine chemische Unkrautbekampfung erforderlich ist, sowie die Zellen mit geringem Risiko, in denen auf eine Unkrautbekampfung verzichtet werden kann. Zu Beginn haben wir eine konventionelle Feldspritze verwendet, die wir spater zu einem Twin Tank mit Direkteinspeisung verandert haben. Von 2008 bis 2016 wurde die Technologie auf 1237 Hektar, 38 Feldern auf insgesamt 2459 Parzellen getestet. Wir konnten fur die neun Jahres-Intervall eine durchschnittliche Herbizideinsparung von 51 % ermitteln. Die Vorteile des entwickelten Verfahrens sind die Wirtschaftlichkeit und die sichere Unkrauterkennung. Der Nachteil ist der hohe Zeitaufwand durch einen Unkrautexperten, da das gesamte Feld abgedeckt werden muss.Als Weiterentwicklung wurde im Jahr 2016 ein autonomes Fahrzeug zur Unkrauterfassung konstruiert. Dies fuhrt zu einer signifikanten Erhohung der Bildanzahl. Die verwendete Office-Umgebung verbessert die Genauigkeit der Bildverarbeitung, die Unkrautartenerkennung und die Ermittlung des Deckungsgrades.